Machine Learning Using Python

Abstract

Machine learning (ML) is a subset of artificial intelligence (AI) that enables software applications to become more accurate at predicting outcomes without explicitly programming them to do so. Machine learning algorithms predict new output values by using historical data as input. In this project, we have used data from the 1994 U.S. Census to model people's income using numerous supervised algorithms of your choice. The best candidate algorithm will then be chosen based on preliminary results, and this algorithm will be further optimized to best model the data. The goal of this implementation is to build a model that accurately predicts whether a person earns more than $50,000. This type of task may arise in a non-profit setting, where Organisations rely on donations to survive this model can be used there. Understanding an individual's income can assist a non-profit in determining how large of a gift to request, as well as whether or not to contact out in the first place. While determining an individual's general income bracket directly from public sources can be challenging, we can deduce this figure from other publicly available information.